Automated estimation of leaf area development in sweet pepper plants from image analysis
Graham W. Horgan A E , Yu Song B , Chris A. Glasbey B , Gerie W. A. M. van der Heijden C D , Gerrit Polder C , J. Anja Dieleman C , Marco C. A. M. Bink C and Fred A. van Eeuwijk CA Biomathematics and Statistics Scotland, Rowett Institute of Nutrition and Health, Aberdeen, AB21 9SB, UK.
B Biomathematics and Statistics Scotland, Kings Buildings, Edinburgh, EH9 3JZ, UK.
C Wageningen UR, Droevendaalsesteeg 1, Wageningen, the Netherlands.
D Present address: DuPont Pioneer, Johnston, IA, USA.
E Corresponding author. Email: g.horgan@bioss.ac.uk
This paper originates from a presentation at the Second International Workshop on Image Analysis Methods for Plant Science, University of Nottingham, 2–3 September 2013.
Functional Plant Biology 42(5) 486-492 https://doi.org/10.1071/FP14070
Submitted: 1 March 2014 Accepted: 28 June 2014 Published: 19 August 2014
Abstract
High-throughput automated plant phenotyping has recently received a lot of attention. Leaf area is an important characteristic in understanding plant performance, but time-consuming and destructive to measure accurately. In this research, we describe a method to use a histogram of image intensities to automatically measure plant leaf area of tall pepper (Capsicum annuum L.) plants in the greenhouse. With a device equipped with several cameras, images of plants were recorded at 5-cm intervals over a height of 3 m, at a recording distance of less than 60 cm. The images were reduced to a small set of principal components that defined the design matrix in a regression model for predicting manually measured leaf area as obtained from destructive harvesting. These regression calibrations were performed for six different developmental times. In addition, development of leaf area was investigated by fitting linear relations between predicted leaf area and time, with special attention given to the genotype by time interaction and its genetic basis in the form of quantitative trait loci (QTLs). The experiment comprised parents, F1 progeny and eight genotypes of a recombinant inbred population of pepper. Although the current trial contained a limited number of genotypes, an earlier identified QTL related to leaf area growth could be confirmed. Therefore, image analysis, as presented in this paper, provides a powerful and efficient way to study and identify the genetic basis of growth and developmental processes in plants.
Additional keywords: Capsicum annuum L., heritability, histogram, principal component analysis, quantitative trait loci.
References
Alimi NA, Bink MCAM, Dieleman JA, Magán JJ, Wubs AM, Palloix A, van Eeuwijk FA (2013) Multi-trait and multi-environment QTL analyses of yield and a set of physiological traits in pepper. Theoretical and Applied Genetics 126, 2597–2625.| Multi-trait and multi-environment QTL analyses of yield and a set of physiological traits in pepper.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC3sflsFeluw%3D%3D&md5=e7800cae05675667d262e3d55f06b535CAS | 23903631PubMed |
Ansley RJ, Price DL, Dowhower SL, Carlson DH (1992) Seasonal trends in leaf-area of honey mesquite trees – determination using image analysis. Journal of Range Management 45, 339–344.
| Seasonal trends in leaf-area of honey mesquite trees – determination using image analysis.Crossref | GoogleScholarGoogle Scholar |
Barchi L, Lefebvre V, Sage-Palloix AM, Lanteri S, Palloix A (2009) QTL analysis of plant development and fruit traits in pepper and performance of selective phenotyping. Theoretical and Applied Genetics 118, 1157–1171.
| QTL analysis of plant development and fruit traits in pepper and performance of selective phenotyping.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXktFektrg%3D&md5=977b7503b3cec0f6f8cab4ac4695ab7dCAS | 19219599PubMed |
Campillo C, Garcia MI, Daza C, Prieto MH (2010) Study of a non-destructive method for estimating the leaf area index in vegetable crops using digital images. Hortscience 45, 1459–1463.
Chauveau J, Rousseau D, Richard P, Chapeau-Blondeau F (2010) Multifractal analysis of three-dimensional histogram from color images Chaos, Solitons, and Fractals 43, 57–67.
| Multifractal analysis of three-dimensional histogram from color imagesCrossref | GoogleScholarGoogle Scholar |
Diebolt KS, Mudge KW (1988) Use of a video-imaging system for estimating leaf surface area of Pinus sylvestris seedlings. Canadian Journal of Forest Research 18, 377–380.
| Use of a video-imaging system for estimating leaf surface area of Pinus sylvestris seedlings.Crossref | GoogleScholarGoogle Scholar |
Kirk K, Andersen HJ, Thomsen AG, Jorgensen JR, Jorgensen RN (2009) Estimation of leaf area index in cereal crops using red–green images. Biosystems Engineering 104, 308–317.
| Estimation of leaf area index in cereal crops using red–green images.Crossref | GoogleScholarGoogle Scholar |
Klemelä J (2009) ‘Multivariate adaptive histograms, in smoothing of multivariate data: density estimation and visualization.’ (John Wiley & Sons, Inc: Hoboken)
Marcon M, Mariano K, Braga R, Paglis C, Scalco M, Horgan GW (2011) Estimation of total leaf area in perennial plants using image analysis. Revista Brasileira de Engenharia Agrícola e Ambiental 15, 96–101.
| Estimation of total leaf area in perennial plants using image analysis.Crossref | GoogleScholarGoogle Scholar |
Mardia KV, Kent JT, Bibby JM (1979) ‘Multivariate analysis.’ (Academic Press: London)
Negrón Juarez RI, da Rocha HR, Figueira AMSE, Goulden ML, Miller SD (2009) An improved estimate of leaf area index based on the histogram analysis of hemispherical photographs. Agricultural and Forest Meteorology 149, 920–928.
| An improved estimate of leaf area index based on the histogram analysis of hemispherical photographs.Crossref | GoogleScholarGoogle Scholar |
Nyakwende E, Paull CJ, Atherton JG (1997) Non-destructive determination of leaf area in tomato plants using image processing. Journal of Horticultural Science 72, 255–262.
Pearce RB, Brown RH, Blaser RE (1965) Relationships between leaf area index, light interception and net photosynthesis in orchardgrass. Crop Science 5, 553–556.
| Relationships between leaf area index, light interception and net photosynthesis in orchardgrass.Crossref | GoogleScholarGoogle Scholar |
Ribeiro KM, Braga R, Scalco M, Horgan GW (2013) Leaf area estimation of medium size plants using optical metrology. Revista Brasileira de Engenharia Agrícola e Ambiental 17, 595–601.
| Leaf area estimation of medium size plants using optical metrology.Crossref | GoogleScholarGoogle Scholar |
Song Y, Glasbey CA, Horgan GW, Polder G, Dieleman A, van der Heijden GWAM (2014a) Automatic fruit recognition and counting from multiple images Biosystems Engineering 118, 203–215.
| Automatic fruit recognition and counting from multiple imagesCrossref | GoogleScholarGoogle Scholar |
Song Y, Glasbey CA, Polder G, van der Heijden GWAM (2014b) Non-destructive automatic leaf area measurements by combining stereo and time-of-flight images. IET Computer Vision
| Non-destructive automatic leaf area measurements by combining stereo and time-of-flight images.Crossref | GoogleScholarGoogle Scholar |
van der Heijden GWAM, Song Y, Horgan GW, Polder G, Dieleman A, Bink M, Palloix A, van Eeuwijk F, Glasbey CA (2012) SPICY: towards automated phenotyping of large pepper plants in the greenhouse. Functional Plant Biology 39, 870–877.
| SPICY: towards automated phenotyping of large pepper plants in the greenhouse.Crossref | GoogleScholarGoogle Scholar |
Voorrips RE, Palloix A, Dieleman JA, Bink MCAM, Heuvelink E, Heijden GWAM, van der Vuylsteke M, Glasbey C, Barócsi A, Magán J, van Eeuwijk FA (2010) Crop growth models for the -omics era: the EU-SPICY project. In ‘Advances in genetics and breeding of capsicum and eggplant. Proceedings of the XIVth EUCARPIA meeting on genetics and breeding of capsicum and eggplant’. (Eds J Prohens, A Rodríguez-Burruezo) pp. 315–321. (Editorial Universidad Politécnica de Valencia: Valencia)
